1. Technical Field
The present invention relates to systems analysis and more particularly, to identifying hidden similarities between such systems.
2. Discussion of the Related Art
In assessing the level of similarity between two given systems, standard correlation analysis is usually used. Such analysis may expose statistical similarities that may in turn point at a similarity in terms of any specified parameter of the two systems. One use of similarity assessment may be found in the systems testing domain. For example, when one computer system in production environment needs to be tested, a similar system may be tested instead, provided that the level of similarity between the two systems is above a specified threshold. Moreover, in the system testing domain, verifying whether a test properly represents the actual system may be crucial.
However, using standard correlation analysis poses a challenge in identifying hidden similarities between two systems. Hidden similarities are situations in which the existing correlation analysis fails to expose similarities in system parametrical terms, although such similarities do exist. One reason for such failure to expose a similarity is that when existing statistical methods expose a similarity, they do not provide an interpretation of the similarity or alternatively, to its absence.
Consequently, existing correlation analysis cannot provide recommendations regarding action that may be taken in order to increase similarity between the given parameters of the systems.